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- Tasks: Design and implement intelligent AI agents to enhance developer workflows.
- Company: Join a fast-growing company leading in engineering innovation and AI automation.
- Benefits: Enjoy fully remote work options and competitive pay starting at £70,000.
- Why this job: Be part of a cutting-edge team driving AI advancements and product innovation.
- Qualifications: Experience with AI frameworks like LangChain and strong programming skills in Python and TypeScript.
- Other info: Ideal for those passionate about ethical AI practices and rapid prototyping.
The predicted salary is between 42000 - 98000 £ per year.
This range is provided by developrec. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from developrec
Head of Global Delivery Centre | Tech Recruitment Partner @ developrec
AI Engineer – Agentic Systems & Automation – £70,000 – Fully remote in UK
A fast-growing company at the forefront of engineering innovation and AI automation is seeking an experienced AI Engineer to help develop intelligent, scalable agentic systems integrated into modern software development lifecycles.
This role involves leading the design and deployment of LLM-powered agents, developer tools, and automation frameworks that streamline workflows and elevate productivity.
This is a hands-on engineering role that blends software development, AI experimentation, and product innovation.
The successful candidate will play a key role in architecting agent-based systems, leveraging advanced frameworks such as LangChain and LlamaIndex, and deploying real-time AI capabilities that integrate deeply with SDLC processes.
Key Responsibilities
- LLM Agent Development: Design and implement intelligent, multi-step agents using frameworks like LangChain, LangGraph, and LlamaIndex to enhance developer workflows.
- Tooling & Assistant Innovation: Develop AI-powered assistants and developer tools with an emphasis on scalability, performance, and reliability.
- AI Engineering: Build, test, and optimize generative AI features using platforms such as OpenAI, Claude, and Gemini, including fine-tuned custom models and evaluation pipelines.
- Prompt Engineering: Design, iterate, and test prompt strategies to improve model accuracy, robustness, and responsiveness across various LLM backends.
- Cross-Functional Collaboration: Work closely with engineering, product, and QA teams to embed agent-led automation within CI/CD pipelines and developer environments.
- Prototyping & R&D: Drive rapid prototyping efforts and validate new ideas through real-world experimentation and user feedback.
- Responsible AI: Promote ethical and secure AI practices, proactively addressing issues like prompt injection, data leakage, and model drift.
- AI Advocacy: Lead internal workshops, demos, and documentation initiatives to promote AI capabilities across teams and client projects.
Ideal Candidate Profile
- Agentic Experience: Proven experience building agent workflows using frameworks such as LangChain, LangGraph, or equivalent.
- AI/ML Expertise: Solid understanding of large language models (LLMs), embeddings, vector search, and prompt engineering.
- Software Engineering Skills: Strong programming skills in Python (AI pipelines) and TypeScript (full-stack integration). Capable of writing production-grade code.
- Product Mindset: Ability to understand user needs and translate them into impactful AI features and experiences.
- Cloud & Data Knowledge: Experience working with cloud platforms (AWS, Azure, or GCP).
- Model Deployment: Familiarity with evaluating, fine-tuning, and deploying LLMs in production environments, including performance monitoring and optimization.
- Collaboration & Agility: Comfortable working in fast-paced, cross-functional teams.
- Experimental Approach: A passion for rapid iteration, learning from experiments, and data-driven development.
Preferred Qualifications
- Experience designing RAG (Retrieval-Augmented Generation) or CAG systems using vector databases and hybrid retrieval techniques.
- Knowledge of LLM security challenges, including prompt injection and adversarial attacks.
- Familiarity with prompt evaluation frameworks and metrics such as truthfulness, helpfulness, and toxicity.
- Hands-on experience with developer-focused AI tools (e.g., Copilot, Cursor), including a deep understanding of their architecture and scalability.
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Job function
Information Technology
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Industries
Software Development and IT System Custom Software Development
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Artificial Intelligence Engineer employer: developrec
Contact Detail:
developrec Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Familiarise yourself with the frameworks mentioned in the job description, such as LangChain and LlamaIndex. Having hands-on experience or even personal projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Engage with the AI community by participating in forums or attending meetups focused on AI and machine learning. Networking with professionals in the field can provide valuable insights and potentially lead to referrals for the position.
✨Tip Number 3
Showcase your understanding of responsible AI practices. Be prepared to discuss how you would address challenges like prompt injection and data leakage during interviews, as this demonstrates your commitment to ethical AI development.
✨Tip Number 4
Prepare to discuss your collaborative experiences in cross-functional teams. Highlight specific examples where you've worked closely with engineering, product, or QA teams to implement AI solutions, as this aligns with the role's requirements.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI engineering, particularly with frameworks like LangChain and LlamaIndex. Emphasise your programming skills in Python and TypeScript, as well as any experience with cloud platforms.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with the responsibilities of the role. Mention specific projects or experiences that demonstrate your ability to design and implement intelligent systems.
Showcase Your Projects: If you have worked on relevant projects, include links or descriptions in your application. Highlight any prototypes or R&D efforts that showcase your experimental approach and understanding of AI tools.
Highlight Collaboration Skills: Since the role involves cross-functional collaboration, mention any experience working in teams, especially in fast-paced environments. Provide examples of how you've successfully collaborated with product and QA teams in the past.
How to prepare for a job interview at developrec
✨Showcase Your Technical Skills
Be prepared to discuss your experience with frameworks like LangChain and LlamaIndex. Bring examples of projects where you've implemented LLM-powered agents or developed AI tools, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Vision
Research the company’s approach to AI and automation. Understanding their goals and how they integrate AI into their software development lifecycle will help you align your answers with their vision during the interview.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills, especially related to AI engineering and prompt engineering. Practice explaining your thought process clearly and concisely, as this will showcase your analytical abilities.
✨Demonstrate Collaboration Skills
Since the role involves cross-functional collaboration, be ready to share examples of how you've worked effectively in teams. Highlight any experiences where you’ve collaborated with product, QA, or engineering teams to achieve a common goal.
